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NASA NTRS2015

Color Changing Hydrogen Sensors

During the Space Shuttle Program, one of the most hazardous operation that occurred was the loading of liquid hydrogen (LH2) during fueling operations of the spacecraft. Due to hydrogen's low explosive limit, any amount leaked could lead to catastrophic event. Hydrogen's chemical properties make it ideal as a rocket fuel; however, the fuel is deemed unsafe for most commercial use because of the inability to easily detect the gas leaking. The increased use of hydrogen over traditional fossil fuels would reduce greenhouse gases and America's dependency on foreign oil. Therefore a technology that would improve safety at NASA and in the commercial sector while creating a new economic sector would have a huge impact to NASA's mission. The Chemochromic Detector for sensing hydrogen gas leakage is a color-changing detector that is useful in any application where it is important to know not only the presence but also the location of the hydrogen gas leak. This technology utilizes a chemochromicpigment and polymer matrix that can be molded or spun into rigid or pliable shapes useable in variable temperature environments including atmospheres of inert gas, hydrogen gas, or mixtures of gases. A change in color of the detector material indicates where gaseous hydrogen leaks are occurring. The irreversible sensor has a dramatic color change from beige to dark grey and remains dark grey after exposure. A reversible pigment changes from white to blue in the presence of hydrogen and reverts back to white in the presence of oxygen. Both versions of the sensor's pigments were comprised of a mixture of a metal oxide substrate and a hydro-chromic compound (i.e., the compound that changed color in the presence of hydrogen) and immediately notified the operator of the presence of low levels of hydrogen. The detector can be used in a variety of formats including paint, tape, caulking, injection molded parts, textiles and fabrics, composites, and films. This technology brings numerous benefits over the traditional hydrogen sensors: The technology has excellent temperature stability (4K to 373 K), it can be used in cryogenic fluid applications, it is easy to apply and remove; it requires no power to operate; it has a quick response time; the leak points can be detected visually or electronically; it is nonhazardous, thus environmentally friendly; it can be reversible or irreversible; it does not require on-site monitoring; has a long shelf life; the detector is very durable; and the technology is inexpensive to manufacture.

Chemochromic sensor↗

DOE OSTI2025

Design and Production for Maximum Structural Efficiency With Respect to Fiber Orientation With Increased Understanding of Hybrid Fiber Flow Behavior

Discontinuous fiber-reinforced thermoplastic composites have gained considerable attention in automotive, aerospace, and other industries, due to their high-rate of production combined with their ability to attain complex and intricate shapes. Among other high-rate thermoplastic manufacturing processes, injection-molding is one of the most common manufacturing methods due to fast production and high surface finishing of complex geometries. Fiber orientation in discontinuous fiber composites plays a pivotal role in determining the mechanical, electrical, and thermomechanical properties, underscoring the necessity to comprehend fiber orientation in injection molded parts. Among different fiber types, glass and carbon fibers are most common in the composite industries. The recent trend of hybrid composites comprising both glass fiber (GF) and carbon fiber (CF) is also gaining importance in the automotive industry. Hybrid fiber options allow designers to optimize the balance between glass and carbon fibers by leveraging the high durability and low cost of GF while the strength and lightweight properties of CF. Consequently, comparing the fiber oriented distribution (FOD) of injection molded composites containing GF, CF, and a hybrid of GF/CF is critical to investigating the local mechanical properties of intricate structures for high-end applications. In Phase I of this project, FOD in injection-molded panels with respect to distance from the gate was analyzed using X-ray computed tomography (X-CT) for GF, CF, and hybrid CF/GF (CGF) reinforced nylon 66. To understand the reason behind the FOD with different fiber types, computational fluid dynamics (CFD) and rheology were performed. Samples were extracted at three locations: near the gate, center, and opposite end. Thickness of the layers of typical skin-shell-core type FOD varies with fiber type and location. GF achieved flow direction alignment (in shell) earlier than viscous CF and CGF near the gate, whereas CF showed the highest flow-direction alignment at the center due to shear induced orientation. At the opposite end, GF experienced more backflow than others indicating faster mold filling owing to its lower viscosity. Hybrid CGF exhibited GF-dominated center and CF-dominated end region. The numerical model used to obtain FOD and rheological predictions for the CF and GF composites served to corroborate the trends observed in the experimental trials. The FOD responses across fiber types and location were reflected in their longitudinal and transverse properties. Only GF showed higher longitudinal modulus over transverse modulus near the gate attributed to rapid alignment, whereas CF and CGF exhibited opposite trend. However, fountain flow enhanced the longitudinal modulus over transverse modulus with the distance for all, particularly for CF. This study offers insights into mold filling behavior of different fibers which are critical in optimizing injection molding conditions for tailored final properties.

36 MATERIALS SCIENCE↗

DOE OSTI2013

In Situ Spectrophotometric Determination of pH under Geologic CO2 Sequestration Conditions: Method Development and Application

Injecting massive amounts of CO2 into deep geologic formations will cause a range of coupled thermal, hydrodynamic, mechanical, and chemical changes. A significant perturbation in water-saturated formations is the pH drop in the reservoir fluids due to CO2 dissolution. Knowing the pH under geological CO2 sequestration conditions is important for a better understanding of the short- and long-term risks associated with geological CO2 sequestration and will help in the design of sustainable sequestration projects. Most previous studies on CO2-rock-brine interactions have utilized thermodynamic modeling to estimate the pH. In this work, a spectrophotometric method was developed to determine the in-situ pH in CO2-H2O-NaCl systems in the presence and absence of reservoir rock by observing the spectra of a pH indicator, bromophenol blue, with a UV-visible spectrophotometer. Effects of temperature, pressure, and ionic strength on the pH measurement were evaluated. Measured pH values in CO2-H2O-NaCl systems were compared with several thermodynamic models. Results indicate that bromophenol blue can be used to accurately determine the pH of brine in contact with supercritical CO2 under geologic CO2 sequestration conditions.

geologic CO2 sequestration, pH measurement, spectr↗

DOE OSTI2026

Differentiable multiphase flow model for physics-informed machine learning in reservoir pressure management

Accurate subsurface reservoir pressure control is extremely challenging due to geological heterogeneity and multiphase fluid-flow dynamics. Predicting behavior in this setting relies on high-fidelity physics-based simulations that are computationally expensive. Yet, the uncertain, heterogeneous properties that control these flows make it necessary to perform many of these expensive simulations, which is often prohibitive. To address these challenges, we introduce a physics-informed machine learning workflow that couples a fully differentiable multiphase flow simulator, which is implemented in the DPFEHM framework with a convolutional neural network (CNN). The CNN learns to predict fluid extraction rates from heterogeneous permeability fields to enforce pressure limits at critical reservoir locations. By incorporating transient multiphase flow physics into the training process, our method enables more practical and accurate predictions for realistic injection-extraction scenarios compared to previous works. To speed up training, we pretrain the model on single-phase, steady-state simulations and then finetune it on full multiphase scenarios, which dramatically reduces the computational cost. We demonstrate that high-accuracy training can be achieved with fewer than three thousand full-physics multiphase flow simulations – compared to previous estimates requiring up to ten million. This drastic reduction in the number of simulations is achieved by leveraging transfer learning from much less expensive single phase simulations.

25 ENERGY STORAGE↗

DOE OSTI2012

PROPAGATION OF GRAVITY WAVES IN A CONVECTIVE LAYER

We perform numerical simulations of gravity mode propagation in a convective layer to investigate the observed association between small spatial scales and low frequencies in the photospheric velocity fields. According to the linear theory, when the fluid layer is convectively unstable, gravity modes are evanescent waves. However, in simple two-dimensional numerical settings, we find that when the equilibrium structure is modified by coherent large-scale convective motions, the waves injected at the bottom of the layer are no longer evanescent. In this situation, gravity waves can be detected at the surface of the layer. In our simplified model the injected wave's frequency remains unchanged, but its amplitude has a spatial modulation determined by the convective structure. This result may explain some analyses done with the proper orthogonal decomposition method of the solar surface velocity field even though solar convection is far more complex than the convection model considered here.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Training Students to Analyze Spatial and Temporal Heterogeneities in Reservoir and Seal Petrology, Mineralogy, and Geochemistry: Implications for CO{sub 2} Sequestration Prediction, Simulation, and Monitoring

The objective of this project was to expose and train multiple students in geological tools that are essential to reservoir characterization and geologic sequestration including but not limited to advanced petrological methods, mineralogical methods, and geochemical methods; core analysis, and geophysical well-log interpretation. These efforts have included training of multiple students through geologically based curriculum and research using advanced petrological, mineralogical, and geochemical methods. In whole, over the last 3+ years, this award has supported 5,828 hours of student research, supporting the work of several graduate and undergraduate students. They have all received training directly related to ongoing CO{sub 2} sequestration demonstrations. The students have all conducted original scientific research on topics related to understanding the importance of lithological, textural, and compositional variability in formations that are being targeted as CO{sub 2} sequestration reservoirs and seals. This research was linked to the Mount Simon Sandstone reservoir and overlying Eau Claire Formation seal in the Illinois Basin- a system where over one million tons of CO{sub 2} are actively being injected with the first large-scale demonstration of anthropogenic CO{sub 2} storage in the U.S. Student projects focused specifically on 1) reservoir porosity characterization and evaluation, 2) petrographic, mineralogical, and geochemical evidence of fluid-related diagenesis in the caprock, 3) textural changes in reservoir samples exposed to experimental CO{sub 2} + brine conditions, 4) controls on spatial heterogeneity in composition and texture in both the reservoir and seal, 5) the implications of small-scale fractures within the reservoir, and 6) petrographic and stable isotope analyses of carbonates in the seal to understand the burial history of the system. The student-led research associated with this project provided real-time and hands-on experience with a relevant CO{sub 2} system, provided relevant information to the regional partnerships who are working within these formations, and provides more broadly applicable understanding and method development for other carbon capture and storage systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Controls on Incomplete Mixing of Injected Raw Water and Brine in Strategic Petroleum Reserve Salt Caverns

Mixing of injected raw (undersaturated) water with brine in Strategic Petroleum Reserve (SPR) salt caverns affects the shape of cavern walls due to leaching. Cavern shape impacts cavern geomechanical stability and available volume for oil storage. Raw water injection occurs during initial solution mining of caverns, remedial leaching of caverns, and oil drawdown. Of interest are factors that control the degree of raw water-brine mixing and thereby the concentration of the aqueous fluid mixture that contacts the salt cavern walls. It is hypothesized that poorly-mixed fresh water could potentially cause undesirable and non-uniform leaching , for example, if buoyant poorly-mixed fresh water collects and preferentially leaches under the oil-brine interface . This report presents current understanding of controls on incomplete-to-complete mixing of raw water and brine, focusing on implications for SPR cavern leaching. In the context of mixing, we review the following: SPR leaching operations; models of leaching; field measurements of leaching and cavern shapes; and previous laboratory experiments of mixing and /or leaching performed at Sandia National Laboratories. We present recent laboratory experiments in 2014-2016 that focused explicitly on understanding controls of poor-to-well mixed conditions. We find that well-mixed conditions are expected for typical operating conditions of the SPR.

04 OIL SHALES AND TAR SANDS↗

NASA NTRS2015

Observation Platform for Dynamic Biomedical and Biotechnology Experiments Using the International Space Station (ISS) Light Microscopy Module (LMM)

Techshot, Inc., has developed an observation platform for the LMM on the ISS that will enable biomedical and biotechnology experiments. The LMM Dynamic Stage consists of an electronics module and the first two of a planned suite of experiment modules. Specimens and reagent solutions can be injected into a small, hollow microscope slide-the heart of the innovation-via a combination of small reservoirs, pumps, and valves. A life science experiment module allows investigators to load up to two different fluids for on-orbit, real-time image cytometry. Fluids can be changed to initiate a process, fix biological samples, or retrieve suspended cells. A colloid science experiment module conducts microparticle and nanoparticle tests for investigation of colloid self-assembly phenomena. This module includes a hollow glass slide and heating elements for the creation of a thermal gradient from one end of the slide to the other. The electronics module supports both experiment modules and contains a unique illuminator/condenser for bright and dark field and phase contrast illumination, power supplies for two piezoelectric pumps, and controller boards for pumps and valves. This observation platform safely contains internal fluids and will greatly accelerate the research and development (R&D) cycle of numerous experiments, products, and services aboard the ISS.

Kurk, Michael A. (Andy)↗

NASA NTRS2015

Observation Platform for Dynamic Biomedical and Biotechnology Experiments Using the International Space Station (ISS) Light Microscopy Module (LMM)

Kurk, Michael A. (Andy)↗

NASA NTRS2018

Hydrovolcanic Astromaterials in the Lab

Zag and Monahans (1998) are H chondrite regolith breccias that contain 4.5 GY old halite crystals which in turn contain abundant inclusions of aqueous fluids, solids and organics. We have previously proposed that these halites originated on a hydrovolcanically-active C class asteroid, probably Ceres, or a trans-neptunian object (TNO - or P- or D-class asteroid) injected into the inner solar system during giant planet migration. We have begun a detailed analysis of organics and other solids trapped within the halite, which we hypothesize sample the mantle of the halite parent object, and are examining a halite-bearing C1 chondrite clast also found in Zag, which is similar to the solids in the halite. These investigations will reveal the water-rock interactions on the hydrovolcanically-active parent world.

Zolensky, M. E.↗

DOE OSTI2019

Validation of Alfvén Eigenmode simulations on DIII-D and Projection for CFETR scenario

Alfvén Eigenmodes (AEs) are driven unstable by on-axis neutral beam (NB) injection in DIII-D reversed magnetic shear discharges #166496 and #159243, a high-beta steady-state demonstration discharge and an L-mode current ramp discharge respectively. Here, the experimental results are used to validate the ideal MHD code with kinetic extensions NOVA-K and the gyro-Landau-fluid code TGLFEP. Both codes predict low toroidal mode number (n=1~2) Toroidal Alfvén Eigenmode (TAE) instability in the former discharge and low-n (n=2~6) Reverse Shear Alfvén Eigenmode (RSAE) instability in the latter discharge, consistent with observations. The same two codes are also employed to predict linear AE instabilities driven by α particles in the China Fusion Engineering Test Reactor (CFETR). For the CFETR reversed shear q profile, the growth rates of AEs change periodically with increasing toroidal mode number and the RSAEs near a rational surface always have larger growth rates than TAEs. AEs are found to be further destabilized by addition of 500keV off-axis injected NB. The effects of q-profile variation on AE stability in CFETR are also investigated and the results show that raising q min can further destabilize RSAEs, while increasing q 0 with fixed q min , to create stronger negative magnetic shear, is stabilizing. Finally, increasing plasma density is beneficial for AE stability due to reduced fast ion drive because of shorter slowing down time and higher electron collisional damping.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Impacts of Pore Network-Scale Wettability Heterogeneity on Immiscible Fluid Displacement: A Micromodel Study

The mixed-wet nature of reservoir formations imposes a wide range of rock wettability from strong resident-fluid wetting to strong invading-fluid wetting. The characteristics of two-phase flow in porous media composed of mixed-wetting surfaces remain poorly understood. In this study, we investigated the displacement of resident ethylene glycol (EG) by hexane in two mixed-wet micromodels of identical 2.5-D geometry heterogeneity, with uniformly or heterogeneously distributed patches strongly wetting to hexane. These patches are mixed among pores with unaltered EG-wetting surfaces. Along with control tests in the originally EG-wet micromodel, here we show the classic fingering and transitions in flow regimes at $logCa$ (capillary number) from -7.2 to -3.9. Moreover, pore-scale distributions of wettability and their spatial correlation influence displacement efficiency. In the two mixed-wet micromodels, we found (a) an increase of steady-state hexane saturation at the end of experiments by up to 0.12 in the capillary fingering regime and a decrease of at most by 0.06 in the viscous fingering regime, compared to the EG-wet micromodel, and (b) dispersed and fragmented hexane distribution after displacement. Brine drainage during supercritical CO 2 (scCO 2 ) injections in these micromodels occurs with lower wettability contrasts, and under similar viscosity ratios and interfacial tensions resulted in higher displacement efficiency relative to displacement of EG by hexane. While mixed-wettability can enhance displacement efficiency compared to uniform wettability, the dynamics of immiscible fluids in strong mixed-wet reservoirs are expected to be less pronounced in contributing to the efficiency of geological CO 2 sequestration, oil recovery, and remediation of hydrocarbon-contaminated aquifers.

2.5-D micromodel↗

DOE OSTI2021

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Demonstration of CFD to support the coupled analysis of a reactor pressure vessel subjected to pressurized thermal shock

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended duration or under accident condition. As one of the most significant components of a reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Aging degradation mechanisms (e.g. thermo-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The prediction of the temperature field is achieved by using computational fluid dynamics (CFD) simulation. In this report, a demonstration CFD standalone simulation is performed to support coupled analysis for Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS). The study use a simplified computational domain to represents a real RPV. The purpose of the study is to demonstrate the transient temperature response of RPV to ECC injection. The CFD model is built in a robust and efficient way for further coupled calculation. The next steps of this work, including the coupled thermal and tensor mechanics capabilities using Cardinal are expected to be complete by the end of FY21 for the demo problem. After this, into FY22, the capability will be demonstrated for a realistic RPV.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Multicycle large-eddy simulations of a direct-injection hydrogen-fueled optical engine

Hydrogen (H 2 ) is a carbon-free chemical energy carrier and one promising solution for achieving effective decarbonization of the transportation sector, particularly for internal combustion engines (ICEs). With a focus on ICEs, and compared to port-fuel injection, direct injection (DI) of gaseous H 2 during the compression stroke offers potential advantages, which include backfire avoidance and reduction of preignition occurrence. In these last two decades, much research, experimental and numerical, has been devoted to understanding H 2 's mixing and combustion processes in ICEs. Computational fluid dynamics modeling efforts commonly rely on unsteady Reynolds-averaged Navier Stokes (URANS) turbulence frameworks, mostly due to their computational affordability. However, many authors have pointed out the opportunity to perform large-eddy simulations (LESs) to investigate the cyclic variability of H 2 engines and assess potential advantages of using LES in place of URANS, especially for lean operation. This study addresses this knowledge gap and presents a computational fluid dynamics (CFD) study of the H 2 DI process in an optical engine operating at relatively low tumble conditions, using multicycle LESs. In conclusion, the manuscript presents a thorough validation of the results against experimental data available from the literature as well as direct comparison with URANS, demonstrating the feasibility of multicycle LESs for CFD modeling of DI H 2 -fueled ICEs.

Direct injection↗

DOE OSTI2021

Numerical Investigation of Enhanced Dehumidification Processes By Using Dielectrophoresis Principles in Moist Airflows

Dispersed particle-laden flows are encountered in many building and industrial applications, such as flow in a fluidized bed, hydrocarbon transportation in pipelines, and the fouling of air-cooled heat exchangers (Kuruneru et al., 2016; Ray et al., 2019; Wang et al., 2019). Computational fluid dynamic (CFD) models have been developed in recent years to depict particle-fluid and particle-particle interactions in laminar or turbulent flows with increasing accuracy and stability. One particular particle-laden system of interest for moisture control is electrically-enhanced condensation in air and water droplet flows. Electrically-enhanced condensation consists of the use of highly charged water droplets injected in the moist air. The droplets become electric seeds that attract polar water vapor molecules to their surfaces and promote condensation. The nucleation and growth of the charged droplets deplete the vapor phase near a droplet, which is compensated for by the dielectrophoresis flow and diffusion. Dielectrophoresis flow involves surrounding vapor at a distance of about 10 to 100 nm for droplets charged by an electrospray compared to ~2 nm for a single electron charge in a droplet. As the vapor molecules collapse on the surface of the droplets, their initial electrical charge decreases with time due to the neutralization of the ions. While the physics of this phenomena is well known, engineering models for predicting the condensation rates are not available. This work computationally investigates dehumidification of moist airflow in a converging rectangular duct. The objective is to develop an engineering model that predicts water vapor condensation by employing dielectrophoresis principles. We construct a Computational Fluid Dynamics (CFD) model of the duct with electrically-enhanced condensation. The model is implemented in the open-source software OpenFOAM. We utilize the Multi-Phase Particle-In-Cell (MP-PIC) method coupled with a Population Balance Equation (PBE) approach to simulate the particle-laden system. This methodology is an Eulerian-Lagrangian approach used to simulate the droplets' behavior in the humid air. The MP-PIC approach (Andrews and O'Rourke, 1996) mitigates the computational cost by parceling several fundamental particles with similar properties (such as types, sizes, and temperature) into one computational particle. Thus, the billions of particles can be substituted by millions of computational particles without significant loss of information. The PBE was considered with the Lagrangian frame to combine the particle distribution function used in MP-PIC (Kim et al., 2020). This approach preserves mass and energy conservation between the phases in the Eulerian and Lagrangian structures. The PBE in this procedure was directly linked to the discrete parcels, making the simulation of the particle distribution computationally efficient and robust. The MP-PIC-PBE approach used in the present work was applied to the dehumidification of air. Water droplets were injected in the air stream and forced to grow according to experimentally derived correlation. The experiments were conducted on a converging duct with the same geometry and boundary conditions used to build the CFD model. This approach enabled us to approximate the effect of dielectrophoresis phenomena on the droplet and air interface. This presentation will discuss the details of the new CFD model built for the duct, the implementation of the model in OpenFOAM CFD programming language, and the experimental validation of the newly developed model. The results revealed a moderate yet measurable increase in droplet diameter due to water vapor condensation at the vapor-liquid interface of the electrically charged droplets' surface. The seed water droplet particles grew in size by capturing the water vapor in the surrounding air. The OpenFOAM model predicted reductions of humidity in the air from 5 to 10 percent.

Yel Mahi, Maliha↗

DOE OSTI2019

Prediction of Alfvén eigenmode energetic particle transport in ITER scenarios with a critical gradient model

A reduced 1D, local, critical-gradient model of energetic particle (EP) transport by Alfvén eigenmodes (AEs)—the TGLF-EP+Alpha model—is applied to a much-studied ITER base case and variations with lower plasma current and lower current penetration. The TGLF-EP+Alpha model is a greatly reduced and computationally inexpensive model of EP transport. Such a reduced critical gradient model, while inapplicable to transport driven by strongly nonlinear or non-local abrupt events, is a valuable tool for scoping studies needed in scenario optimization for ITER and beyond. Furthermore, it relies on the assumption of critical-gradient AE transport with the critical EP density gradient determined by linear AE stability calculations in the TGLF gyro-Landau fluid code automated with the parallel-processed TGLF-EP wrapper. EP transport is treated with simultaneous drive of AEs by fusion-born alpha particles and fast ions born from a 1 MeV neutral beam injection (NBI) heating. The effect of simultaneous drive creates about 50% increased particle transport in both EP channels. High magnetic safety factor q and low shear $\hat{s}$ are generally destabilizing to AEs, but low shear tends to be more important. A tailored q-profile, steady-staterelevant scenario can reduce AE-induced EP redistribution by better than 25% over the ITER base case despite having half the total current.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1987

Liquid Engine Jet Atomization Workshop report

The workshop was oriented to disclose information and unsettled problems to understand the fundamental physical mechanism of the droplet formation process. Based on presentation and discussion of results, recommendations were made which should lead to associated future activities. To accomplish this task, existing observations and experiments, contributing to the basic knowledge, providing data for analytical concept verification, and forming a basis for empirical correlations were solicited. Advanced analytical modeling methods or results from specific studies were requested as well as the experience and advice from injector designers. All effort is directed to advance current analytical techniques, simulating the flow behavior downstream of the injection elements in a liquid rocket combustion chamber. Such a tool can be used to optimize injector designs with respect to short length weight savings, wall material protection, or large heat energy transport to a regenerative cooling fluid, while simultaneously achieving the maximum specific impulse in performance. The liquid atomization process also forms a sound basis for combustion instability analysis.

Gross, Klaus W.↗